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Traditionally, most readers' news access and consumption were based on direct intentional news seeking behavior. However, in recent years the emergence and popularization of social media platforms have enabled new opportunities for citizens to be incidentally informed about public affairs and politics as by-product of using these platforms. This article seeks to shed light on how socio-political conversation attributes may explain incidental exposure to information.

Drawing on US and UK survey data, the authors explore the role of political discussion and discussion network heterogeneity in predicting individuals' levels of incidental exposure to news. Furthermore, the authors also test the role of social media news use as a moderator. A hierarchical OLS regression analysis with incidental news exposure as dependent variable was conducted as well as analyses of moderation effects (heterogeneity*social media and political discussion*social media) using the PROCESS macro in SPSS.

Findings reveal that heterogeneous networks are positively related to incidental news exposure in the UK, while sheer level of political discussion is a positive influence over incidental news exposure in the US. Social media news use moderates the relationship between political discussion and incidental news exposure in the UK. That is, those who are highly exposed to news on social media and discuss less often about politics and public affairs, they tend to be incidentally exposed to news online the most. Meanwhile, the interaction of social media news and discussion heterogeneity showed significant results in the US with those exhibiting high levels of both also receiving the biggest share of INE.

This study contributes to closing research gaps regarding how and when people are inadvertently exposed to news in two Western societies. By highlighting that beyond the fate of algorithmic information treatment by social media platforms, discussion antecedents as well as social media news use play an integral part in predicting incidental news exposure, the study unravels fundamental conditions underlying the incidental news exposure phenomenon.

The purpose of this study is to identify the structural processes that lead citizens to escape their common social circles when talking about politics and public affairs (e.g. “filter bubbles”). To do so, this study tests to what extent political attitudes, political behavior, news media consumption and discussion frequency affect discussion network heterogeneity among US citizens.

Supported by the polling group Nielsen, this study uses a two-wave panel online survey to study the antecedents and mechanisms of discussion network heterogeneity among US citizens. To test the hypotheses and answer the research questions, ordinary least squares (OLS) regressions (cross-sectional, lagged and autoregressive) and mediation analyses were conducted.

The findings imply that political discussion frequency functions as the key element in explaining the mechanism that leads politically interested and participatory citizens (online) as well as news consumers of traditional and online media to seek a more heterogeneous discussion network, disrupting the so-called “filter bubbles.” However, mediation analyses also showed that discussion frequency can lead to more homogenous discussion networks if people score high on political knowledge, possibly reflecting the formation of a close network of political-savvy individuals.

The survey data give important insights into the 2016 pre-election situation, trying to explain why US citizens were more likely to remain in homogenous discussion networks when talking about politics and public affairs. By using two-wave panel data, the analyses allow to draw tentative conclusions about the influential and inhibiting factors and mechanisms that lead individuals to seek/avoid a more heterogeneous discussion network.

In the past few years, research focusing on misinformation, referred to broadly as fake news, has experienced revived attention. Past studies have focused on explaining the ways in which people correct it online and on social media. However, fewer studies have dealt with the ways in which people are able to identify fake news (i.e. fake news literacy). This study contributes to the latter by theoretically connect people’s general social media use, political knowledge and political epistemic efficacy with individuals’ fake news literacy levels.

A diverse and representative two-wave panel survey in the United States was conducted (June 2019 for Wave 1, October 2019 for Wave 2). We performed cross-sectional, lagged and autoregressive regression analyses to examined how social media us, people’s political knowledge and political epistemic efficacy are related to their fake news literacy.

Results suggest that the more people used social media, were politically knowledgeable and considered they were able to find the truth in politics (i.e. epistemic political efficacy), the more likely they were to discern whether the news is fake. Implications of helping media outlets and policy makers be better positioned to provide the public with corrective action mechanisms in the struggle against fake news are discussed.

The measurement instrument employed in the study relies on subjects’ self-assessment, as opposed to unobtrusive trace (big) digital data, which may not completely capture the nuances of people’s social media news behaviors.

This study sheds light on how the way people understand politics and gain confidence in finding political truth may be key elements when confronting and discerning fake news. With the help of these results, journalists, media outlets and policymakers may be better positioned to provide citizens with efficient, preemptive and corrective action mechanisms in the struggle against misinformation.

Recent literature highlights the importance of literacy education to contest fake news, but little is known about what specific mechanisms would contribute to foster and reinvigorate people’s fake news literacy. This study helps address this gap.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-03-2024-0140

Gender and geographical imbalance in production and impact levels is a pressing issue in global knowledge production. Within Health Sciences, while some studies found stark gender and geographical biases and inequalities, others found little empirical evidence of this marginalization. The purpose of the study is to clear the ambiguity concerning the topic.

Based on a comprehensive and systematic analysis of Health Sciences research data downloaded from the Scival (Scopus/Scimago) database from 2017 to 2020 (n = 7,990), this study first compares gender representation in research productivity, as well as differences in terms of citation per document, citations per document view and view per document scores according to geographical location. Additionally, the study clarifies whether there is a geographic bias in productivity and impact measures (i.e. citation per document, citations per document view and view per document) moderated by gender.

Results indicate that gender inequalities in productivity are systematic at the overall disciplinary, as well as the subfield levels. Findings also suggest statistically significant geographical differences in citation per document, citations per document view, and view per document scores, and interaction effect of gender over the relation between geography and (1) the number of citations per view and (2) the number of views per document.

This study contributes to scientometric studies in health sciences by providing insightful findings about the geographical and gender bias in productivity and impact across world regions.